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Update README.md

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@@ -55,8 +55,8 @@ You can use this model directly with a pipeline for text generation.
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  >>> from transformers import pipeline
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  >>> generator = pipeline('text-generation', model="facebook/opt-2.7b")
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- >>> generator("Hello, I'm am conscious and")
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- [{'generated_text': 'Hello, I am conscious and I am a human being.\nI am a human being, and'}]
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  ```
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  By default, generation is deterministic. In order to use the top-k sampling, please set `do_sample` to `True`.
@@ -66,8 +66,8 @@ By default, generation is deterministic. In order to use the top-k sampling, ple
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  >>> set_seed(32)
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  >>> generator = pipeline('text-generation', model="facebook/opt-2.7b", do_sample=True)
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- >>> generator("Hello, I'm am conscious and")
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- [{'generated_text': "Hello, I'm am conscious and I make things. I'm in the creative community, which is"}]
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  ```
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  ### Limitations and bias
 
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  >>> from transformers import pipeline
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  >>> generator = pipeline('text-generation', model="facebook/opt-2.7b")
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+ >>> generator("What are we having for dinner?")
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+ [{'generated_text': 'What are we having for dinner?\nI'm thinking pizza.\nI'm thinking tacos.\n'}]
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  ```
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  By default, generation is deterministic. In order to use the top-k sampling, please set `do_sample` to `True`.
 
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  >>> set_seed(32)
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  >>> generator = pipeline('text-generation', model="facebook/opt-2.7b", do_sample=True)
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+ >>> generator("What are we having for dinner?")
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+ [{'generated_text': "What are we having for dinner?\nJust pizza?\nWell, I suppose that would suffice."}]
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  ```
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  ### Limitations and bias